Research ArticleArticles

Detection of Ganoderma australe Decay in Three Acacia confusa Trees: A Case Study

Cheng-Jung Lin, Po-Hong Lin, Chieh-Yu Chang and Qi-Zhu Gong
Arboriculture & Urban Forestry (AUF) March 2025, 51 (2) 154-168; DOI: https://doi.org/10.48044/jauf.2025.003

Abstract

Background This study aims to utilize various nondestructive methods to assess the internal trunks of 3 Acacia confusa trees affected by Ganoderma australe decay.

Methods Visual Tree Assessment (VTA) was employed to examine the trees, selecting 3 Taiwan acacia (Acacia confusa) trees at the base of which G. australe fungal fruiting bodies were growing, identified as severely damaged and classified as having an immediate hazard level. Subsequently, a stress wave device was used to detect the cross-sectional area of these trees at the locations where G. australe fungus was growing in order to obtain 2D tomographies of stress wave velocity. Following this, a resistance drilling instrument was used to examine the same cross-sectional areas, acquiring resistance drilling amplitude data. Finally, the 3 trees were felled, and 15-cm thick discs were cut from the same cross-sectional areas for laboratory testing.

Results Using 2D sonic tomography and a corresponding velocity grid map of stress wave velocity revealed areas with varying velocities across the trunk cross sections. Drill resistance profile curves depicted changes in resistance strength, while visual inspections of disk cross sections indicated the location and severity of decay. Additionally, pilodyn penetration testing showed different penetration depths on the surfaces of the disk cross sections.

Conclusion The study discusses the use of these detective methods to discover the location and extent of decay within tree trunks and assesses the percentage of decay in cross-sectional areas, providing a reference for tree risk assessment levels.

Keywords

Introduction

In 2024, an unexpected collapse of a Taiwan acacia (Acacia confusa) on the campus of Tunghai University in Taiwan resulted in one fatality. Subsequent investigations of nearby standing A. confusa trees revealed the presence of Ganoderma australe fungal fruiting bodies at the bases of their trunks, which typically signifies immediate risk to trees based on visual tree assessment (VTA) criteria. However, the extent of internal decay caused by G. australe invading the tree trunks from the outside remains unclear and lacks scientific data to support it. Because the state of tree decay at any given time is the result of a dynamic interaction between the host and the fungus, we can only use various existing nondestructive and destructive techniques to detect and determine the degree and extent of decay in a specific tree species based on the current presence of certain fungal fruiting bodies. The results obtained from these techniques serve as reference points for further analysis.

Internal decay or hollowing within trees is a primary cause of tree collapse or breakage. Trees with compromised structure are vulnerable to damage during strong winds or heavy rain, potentially leading to public safety incidents. Visual tree assessment methods are typically the starting point for tree defect evaluations, but relying solely on visual inspection makes it difficult to assess internal defects within tree trunks, which is detrimental to tree risk assessment and management (Pokorny et al. 2003; Juhásová et al. 2007; Lin et al. 2008; Luley 2022).

Apart from VTA methods, nondestructive techniques provide means to detect internal defects within tree trunks. Among these, sonic tomography offers insights into the entire cross section of trees. Consequently, numerous studies have explored the accuracy and practicality of this method, aiming to enhance its applicability. However, its accuracy can be influenced by the wood properties of different tree species (Brazee et al. 2011; Tallavo et al. 2012; Gilbert et al. 2016; Karlinasari et al. 2016; Ostrovský et al. 2017). Acoustic tomography is still influenced by the characteristics of wood in different tree species. Therefore, the acoustic wave propagation path of the sensor needs further exploration to improve the detection and evaluation of decay. Additionally, other nondestructive techniques can be applied for multiple inspections to achieve more accurate assessments of tree decay.

Sonic tomography has been extensively investigated for decay detection in urban trees and stability assessments (Wang et al. 2005; Liang et al. 2008; Wang and Allison 2008; Wang et al. 2009; Johnstone et al. 2010; Son et al. 2021). In surveys of urban trees, the use of sonic tomography has shown concrete results in detecting moderate to severe internal decay (Li et al. 2012). Understanding the weakest parts within tree trunks and their positions in the trunk structure is crucial for assessing the risk of trunk breakage (Heikura et al. 2008).

Sonic tomography provides information on the wood quality of tree trunks, yet discrepancies remain in distinguishing decayed wood, bacterial wet wood, decayed wood with hollows, or boundary areas (Johnstone et al. 2010). Generally, decay presence in wood reduces sound velocity due to decreased overall density, which applies to most common wood decay fungi. However, fungi like Kretzschmaria deusta may have minimal impact on sound transmission time, making it challenging for sonic tomography to detect such decay. Moreover, decay fungi vary in their ability to decompose sapwood (Rayner and Boddy 1988; Rabe et al. 2004). Some species cause aggressive lateral decay and invade sapwood, while others induce more stable and predictable heartwood decay (Terho et al. 2007). Wood decay in standing trees is closely related to human safety; however, not all fungi pose the same level of risk to trees. For instance, trees may not be at risk of mechanical failure if only a small volume of decay is found or if the tree is infected by less aggressive invasive decay fungi (Deflorio et al. 2008). Therefore, different decay fungi species and their decay patterns within tree trunks may vary. Reported descriptions and scientific figures on the typical infection patterns and decay progression of G. australe on A. confusa are currently lacking.

Most studies using diagnostic equipment have primarily focused on detecting decayed wood in the central portions of tree trunks (Gilbert and Smiley 2004; Kaestner and Niemz 2004; Rabe et al. 2004; Wang et al. 2005). However, there is limited research data on detecting decay patterns progressing from the outer circumference of tree trunks towards the interior stages (Deflorio et al. 2008). There are also few studies on the development of fungal fruiting body decay from sapwood decay to heartwood decay in trees.

Sonic tomography assessment of internal tree trunk accuracy is influenced by various factors. In these cases, complementary nondestructive techniques such as drilling resistance tests are needed to determine defect characteristics and aid in correctly interpreting tomographic images. Drilling resistance measures relative resistance within materials (fixed drilling speed), where a rotating drill bit (3-mm tip diameter, 1.5-mm shaft diameter) penetrates wood at a constant speed, displaying changes in resistance profile on a graph. Continuously low resistance areas indicate decay, hollows, or cracks. Due to the need for drilling into trees, this test is considered minimally invasive. Owing to its high accuracy, drilling resistance is widely employed in decay detection or timber structure assessment (Allison and Wang 2015; Frontini 2017; Karlinasari et al. 2017; Downes et al. 2018; Fundova et al. 2018; Sharapov et al. 2018; Sharapov et al. 2020).

In addition, pilodyn is a portable device used to assess the density of living trees (plantation tree) and timber (beams and columns). In pilodyn, a springloaded striker pin is driven into the wood and the penetration depth is measured. The pin penetration depth is inversely correlated with wood density (Seta et al. 2021; Yasuda et al. 2021). Pilodyn penetration testing is minimally invasive as it requires only a small hole to be drilled into the wood to assess wood density, without causing significant damage to the wood or tree.

The objective of this study was to inspect G. australe fungal fruiting bodies on the trunks of A. confusa trees using VTA methods. Additionally, stress wave testing will be employed to assess the interior of the trunks and generate 2D tomographies of stress wave velocities, followed by the creation of corresponding 2D velocity grid maps to understand stress wave velocity values in different areas. Subsequently, the drilling resistance method will be used to test resistance amplitude variation profiles on the trunks, to assess the extent and location of decayed and non-decayed regions. Finally, visual inspections of disks obtained from felled trees will be conducted to understand the decay conditions in cross sections. Additionally, pilodyn penetration testing will be used to assess the depth of penetration and evaluate the extent of decay at different locations. Through these methods, we aim to understand the extent and severity of G. australe decay on the cross sections of A. confusa trees, serving as a basis for tree risk assessment.

Materials and Methods

Experimental Procedure

The experiment was conducted in the campus environment of Tunghai University in Taichung, targeting A. confusa trees. First, after selecting 3 A. confusa trees (numbered on campus as No. 47, 51, and 86) at the base of which G. australe fruiting bodies were growing, VTA was employed to examine the trees. The trees were selected for experiments and disks were harvested with the consent of the tree management unit. These trees were assessed as severely damaged and classified as having an immediate risk level. Subsequently, a stress wave device was used to detect the cross-sectional area of these trees at the locations where G. australe fungus was growing, in order to obtain 2D tomographies of stress wave velocity. Following this, a resistance drilling instrument was used to examine the same cross-sectional areas, acquiring resistance drilling amplitude data. Finally, the 3 trees were felled, and 15-cm thick discs were cut from the same cross-sectional areas for laboratory testing. The cross-sectional discs were taken from the most severely damaged part of the tree trunk, where the G. australe fungus was present. In the laboratory, a grid map of 4 × 4-cm squares was drawn on the cross-sectional surface of the discs, and a pilodyn detector (spring strength 6J, plunger diameter 2.5 mm) was used to strike the center of each small square, measuring the penetration depth of the plunger into the wood surface. The pilodyn instrument is a destructive application, and the greater the penetration depth, the greater the decay.

Sonic Tomography

Sonic tomography was conducted using the Fakopp 3D stress wave detection system v6.5 (Fakopp Enterprise Bt., Agfalva, Hungary) to construct 2D tomographic images of cross sections at the sites of G. australe infections in 3 trees. The instrument and software were operated according to the operating manual (FAKOPP 2020). However, to facilitate comparison and avoid the bias associated with irregular shapes, the cross section of the tree trunk was standardized to a circular shape. The transmission time and acoustic velocity of the stress wave method were measured to obtain raw data for processing into 2D tomography. The Fakopp 3D tomography device consists of 8 sensors placed on the horizontal plane of the tree trunk cross section. These sensors were arranged equidistantly around the circumference of the tree trunk cross section.

The cross sections of the 3 sampling disks were irregular in shape. Since the geometric shapes were all different, using software to formulate different shapes for evaluation and scanning could have led to differences in geometric shapes and caused further misunderstandings, making it difficult to explain the results. Therefore, this study uniformly used the geometric shape of a circle to measure cross sections. Although this had limitations in evaluation, using a circle made it easier to understand the evaluation assuming each symmetrical orientation. The stress wave velocity values were combined with the drilling resistance method to double-check the location and condition of decay.

Under the operation of ArborSonic 3D software (Fakopp Enterprise Bt., Agfalva, Hungary), the stress wave velocity 2D tomographies of the cross sections were drawn. Data on sonic transmission were collected by repeatedly striking each sensor with a steel hammer, gathering a complete data matrix at each test location. The software automatically calculated the stress wave velocity values to obtain the 2D tomographies of transverse stress wave velocity.

The Fakopp stress wave tomography system was used to conduct sonic tomography tests on A. confusa trees. The surface of an A. confusa tree trunk with G. australe is shown in Figure 1A, along with the sensor arrangement, sonic measurement paths, and 2D tomographies of stress wave velocity (in gray) in Figure 1B. The transverse stress wave velocity 2D tomography with the corresponding stress wave velocity grid map (40 mm × 40 mm) are shown in Figure 1C and Figure 1D.

Figure 1.
Figure 1.

Sonic tomography test on Acacia confusa using a Fakopp stress wave tomographic tool. (A) Ganoderma australe on the trunk surface of Acacia confusa. (B) Sensor arrangement, sonic measurement paths, and stress wave velocity tomography (gray). (C) Schematic of the stress wave velocity grid map. (D) The corresponding velocity grid map (40 mm × 40 mm).

Drilling Resistance

A drilling resistance device (IML-RESI PowerDrill® PD200; IML Electronic, Rostock, Germany) was used to test the cross sections of tree trunks at the locations infected with G. australe in the east, south, west, and north directions. Drilling was performed from the bark towards the pith to obtain drilling resistance amplitude profiles. The purpose was to compare and correlate these profiles with the 2D tomographies and the surface of the trunk cross-section discs, to understand the nondecayed and decayed areas of the cross section. The drilling resistance parameters were set to obtain one resistance amplitude value every 0.1 mm, with a drilling feed rate of 200 cm/min and a drill rotation speed of 2,500 RPM.

Results

Stress Wave Detection

A stress wave device was used to detect the cross sections of 3 A. confusa trees, obtaining 2D tomographies of transverse stress wave velocity and the corresponding transverse stress wave velocity grid maps, as shown in Figure 2 through Figure 4 (A and B). The green, yellow, and red colors represent areas of high to low stress wave velocities, respectively. Visual inspection revealed that the red areas indicate severely decayed wood, while the green areas represent less affected wood. Table 1 shows the highest, lowest, and average stress wave velocities for the 3 cross sections. The highest stress wave velocities ranged from 1,570 to 1,915 m/s; the lowest ranged from 699 to 769 m/s; and the average ranged from 1,131 to 1,228 m/s. The lower the stress wave velocity, the more severe the wood decay. According to calculations after software operation, the relative velocity decrease and estimated decayed area for trees No. 51, 47, and 86 were 50%, > 50%, > 50%; and 54%, 47%, and 50%, respectively.

Figure 2.
Figure 2.

(A) Transverse stress wave velocity tomography (green-yellow-red). (B) Corresponding velocity grid map (40 mm × 40 mm). (C) Drilling resistance amplitude (%) profiles. (D) Surface of disk cross section. (E) Penetration depth (mm) for Acacia confusa No. 51.

Figure 3.
Figure 3.

(A) Transverse stress wave velocity tomography (green-yellow-red). (B) Corresponding velocity grid map (40 mm × 40 mm). (C) Drilling resistance amplitude (%) profiles. (D) Surface of disk cross section. (E) Penetration depth (mm) for Acacia confusa No. 47.

Figure 4.
Figure 4.

(A) Transverse stress wave velocity tomography (green-yellow-red). (B) Corresponding velocity grid map (40 mm × 40 mm). (C) Drilling resistance amplitude (%) profiles. (D) Surface of disk cross section. (E) Penetration depth (mm) for Acacia confusa No. 86.

View this table:
Table 1.

Transverse stress wave velocities (m/s) in tomographies of 3 different decay-damaged Acacia confusa trees. V (velocity); DP (decay percentage).

Drilling Resistance Detection

Using a drilling resistance device, the cross sections of 3 A. confusa trees were examined. Drilling was performed from the north, west, south, and east directions of the trees, moving from the bark towards the pith. The profiles of drilling resistance amplitude changes were obtained, as detailed in Figure 2 through Figure 4C. The results indicated that lower drilling resistance amplitudes corresponded to more severe wood decay, while higher amplitudes indicated less affected wood. These results can be correlated with the optical photographs of the cross sections.

The drilling resistance amplitude profiles were divided into nondecayed and decayed sections, with their averages detailed in Table 2. The average drilling resistance amplitude for nondecayed sections ranged from 33.5% to 51.1%, while for decayed sections, it ranged from 2.6% to 27.0%. The t-test showed a significant difference between the 2. Due to the irregular decay pattern caused by fungal fruiting bodies, some sections of the drilling resistance amplitude profiles could not completely distinguish the decayed areas, resulting in a larger standard deviation (6.7% to 16.5%) for the nondecayed areas.

View this table:
Table 2.

Drilling resistance amplitude (%) of 3 different decay-damaged Acacia confusa trees. UDW (undamaged wood); DW (decayed wood); DP (decay percentage).

Through sonic tomography and resistance drilling methods, the thicknesses of intact wood in the cross sections of the trunks were detected. The decayed and intact parts could not be mapped to the corresponding positions. In addition to the irregular shapes of the trunks, the acoustic velocity could still travel (transmission) through the wood due to different degrees of decay. As a result, the decay areas estimated (from software) by the sonic tomography method were lower than the results of the resistance drilling method. For trees No. 51, 47, and 86, the estimated decay areas were 54%, 47%, and 50%, compared to 76.8%, 61.7%, and 67.3%, respectively.

Examination of Cross-Sectional Discs

The trunks of 3 A. confusa trees, including the regions with G. australe fruiting bodies, were cut into discs for visual inspection. The results are detailed in Figure 2 through Figure 4D. The inspection showed that G. australe decay began from the bark on the outer circumference of the trunk and gradually extended to almost the entire heartwood region. The degree of decay was irregular and visibly apparent, but the severity of the decay could not be determined through visual inspection alone.

Using a magnifying glass, observations were made on the trunk cross sections, including the sapwood, heartwood, decayed parts, and the interface between the wood and decayed areas (Figure 5). The results indicated that the heartwood was more significantly affected by decay. The boundary of the decayed heartwood exhibited various levels of Compartmentalization of Decay in Trees (CODIT), forming reaction zones. In some areas, the decay penetrated these reaction zones, leading to irregular decay patterns.

Figure 5.
Figure 5.

Photos of sapwood (SW), heartwood (HW), undamaged (UDW), decayed (DW), and CODIT wood in cross-sectional surfaces.

In the CODIT defense mechanism of the decayed acacia tree, after surface treatment of the cross section of the trunk, we observed with the naked eye that there were obvious dark stripes at the boundary between decayed and intact wood (Figure 5), which were darker than the color of the heartwood. These reaction zones, approximately 2 to 3-mm wide, were thought to be the result of the accumulation of secondary metabolites in the tree, but this was not detected by further chemical analysis. Judging their physical strength from the magnitudes of the drilling resistance amplitudes, we found that there were higher drilling resistance amplitude values in the realms of decayed and intact wood (Figure 2 through Figure 4C). Additionally, on the cross section, some reaction zones were further invaded by decay fungi, resulting in irregular and varying degrees of decay.

Pilodyn Penetration Testing

The pilodyn device was used to impact the surface of the cross-sectional discs with its striker pin, measuring the penetration depth as a standard. Greater penetration depth indicated more severe wood decay, while shallower penetration depth indicated less decay. The results of the cross-sectional penetration depth grid map are detailed in Figure 2 through Figure 4E. The cross sections were divided into nondecayed and decayed areas, and their average penetration depths are shown in Table 3. The average penetration depth for nondecayed areas ranged from 9.49 to 11.30 mm, while for decayed areas, it ranged from 36.48 to 42.64 mm. There was a significant difference between these values based on t-test results. The grid size for the cross-sectional penetration depth map was 4 × 4 cm. For areas with obvious decay and nondecayed wood, the impact penetration depth was measured separately.

View this table:
Table 3.

Penetration depth (mm) in disc cross section of 3 different decay-damaged Acacia confusa trees using Pilodyn. UDW (undamaged wood); DW (decayed wood); DP (decay percentage).

Discussion

With the consent of the tree management unit, 3 A. confusa trees with G. australe fruiting bodies were selected for experiments and harvesting. Consequently, this study relied on only 3 sample trees to characterize the effects of G. australe on the decay of A. confusa, which presents certain limitations. Therefore, this report focuses on a specific type of fungal decay as a case study for illustration.

To understand the reference for the reduction rate between the reference velocity value and the measured velocity value, we compared the absolute velocity values of different tree species. Regarding the average minimum stress wave velocity for sound (nondecayed) wood in tree trunks, relevant literature reports the following: Norfolk Island pine (Araucaria heterophylla) at 1,129 to 1,296 m/s (Lin et al. 2015); Japanese cedar (Cryptomeria japonica) at 1,354 m/s (Lin et al. 2016c); hoop pine (Araucaria cunninghamii) at 1,154 m/s (Lin et al. 2016b); ironwood (Casuarina equisetifolia) at 1,636 m/s (Lin et al. 2016a); and camphor (Cinnamomum camphora) at 1,543 m/s (Lin et al. 2023). This study does not provide the stress wave velocity for completely unaffected A. confusa tree cross sections. According to previous research conducted on ironwood, the boundary range between decayed and nondecayed wood is approximately 1,461 to 1,636 m/s (Lin et al. 2016a). Therefore, this study uses a transverse stress wave velocity of 1,400 m/s as the standard boundary between decayed and nondecayed wood. Based on this standard, the percentage of decayed area for the 3 cross sections was calculated as 68.4% (No. 51); 85.0% (No. 47); and 65.4% (No. 86). The reduction in stress wave velocity indicates severe damage, and its location and extent can be observed in the stress wave velocity grid map.

Some studies indicate that stress wave or ultrasonic tomography cannot accurately assess the extent and location of decay or defect types (Wang et al. 2007; Wang et al. 2009). For example, stress wave and ultrasonic tomography may underestimate internal decay in the central part of the trunk and overestimate decay in the peripheral outer part of the trunk. Some studies have highlighted the impact of cross-sectional geometry on the accuracy of sonic tomography (Soge et al. 2020; Li et al. 2022). The shape of the cross section affects the accuracy of acoustic tomograms; deviations from a circular outline generally lead to reduced accuracy. Additionally, the number of sensors used naturally influences the accuracy of the measurements (Rabe et al. 2004). The use of a simplified circular geometry in this study may account for some of the observed inaccuracies. For certain devices, accuracy also depends on the number of intersecting acoustic propagation paths at a given location. Since more intersections occur in the center of the stem, accuracy tends to be lower at the periphery of the section.

To address this, while the use of a circular shape simplifies the analysis, it introduces potential inaccuracies. However, using irregular shapes could also result in deviations due to geometric complexities. Therefore, the choice of a circular shape was made to strike a balance between simplicity and potential deviations in the results. Further research could explore the comparative impact of different geometries on measurement accuracy to optimize the methodology.

Alternatively, detecting decay in the central part of the trunk may be more suitable than detecting decay in the peripheral part (Deflorio et al. 2008). Additionally, using hardness mapping and sonic tomography to detect decay in the heartwood area of the trunk shows that sonic tomography underestimates the area of decay (Liang et al. 2008). The frequency of the stress wave is influenced by various factors, including the wood material, the applied sensor, and the geometry, such as the distance between the source and the receiver (Ostrovský et al. 2017). When tomography is used to assess structural defects in a trunk, the presence of internal cracks or ring cracks can lead to an overestimation of the defect area. This overestimation is often due to the improper distance between probes, which affects the accuracy of the stress wave measurement. Essentially, the accuracy of tomography is dependent on the correct setup of these parameters to avoid misrepresenting the size and extent of structural defects. Defects or decay areas can only be detected when they account for more than 2.8% to 5% of the cross-sectional area (Ostrovský et al. 2017). Therefore, to better assess the internal condition and decay of trees, other more effective methods should be combined, such as using more probe sensors to improve resolution.

Sonic tomography only reflects the sonic properties of the tested cross section, not the actual internal condition. Therefore, conducting drilling resistance tests under the guidance of the information provided by tomography can more accurately distinguish between decayed wood and cracks indicated by the tomographies (Wang and Allison 2008). The drilling resistance technique or core sampling by increment borers to determine the location and nature of defects can improve the accuracy of the information. However, these minimally invasive methods can disrupt the tree’s compartmentalization defense mechanism, breaking the existing reaction barriers within the tree, potentially allowing decay to spread into nondecayed wood. Therefore, when using decay detection equipment, the number of drilling or sensor locations should be kept to a minimum.

Severe wood decay can reduce stress wave velocity to 70% of the characteristic values of sound wood, indicating a significant decline in strength (Bethge et al. 1996). Additionally, if the stress wave velocity (Fakopp) drops below 90% to 85% of the average speed, cavities or decay may be present. When the relative velocity decrease is 0%, 5%, 10%, 15%, 20%, 30%, 40%, 50%, and > 50%, the estimated decayed area is 0%, 0%, 0%, 0% to 10%, 10% to 20%, 10% to 20%, 20% to 40%, 30% to 50%, and > 50%, respectively (FAKOPP 2020). As stress wave velocity decreases, the area and extent of decay and cavities become more severe (Ostrovský et al. 2017). In this study, lower drilling resistance amplitude profiles were observed in the cross sections of decayed trees. To distinguish between decayed and nondecayed wood, a threshold value of 70% of the average drilling resistance amplitude of nondecayed wood was used, with a threshold range of 23.5% to 35.8%. According to this standard, drilling resistance amplitudes below this threshold are considered indicative of wood decay. Using this method, the percentages of decayed areas in the cross sections were calculated to be 76.8% (No. 51), 61.7% (No. 47), and 67.3% (No. 86).

Visual inspection and examination under a magnifying glass can determine the presence of decay in the cross sections of tree trunks based on color and tissue characteristics (Figure 2 through Figure 4D and Figure 5). However, it is challenging to assess the severity of the decay, particularly when the irregularity ofthe decay leads to uneven degradation of wood density. This is especially true when observing the reaction zones formed by the CODIT mechanism (Shigo 1989; Mattheck and Breloer 1994). The samples showed varying degrees of compartmentalization, forming reaction zones in the heartwood. Additionally, the heartwood was more affected by decay compared to the sapwood, as the sapwood has greater resistance to decay during the tree’s growth phase.

In this study, the pilodyn penetration depth (grid map) was observed to be greater in decayed wood cross sections. To differentiate between decayed and nondecayed wood, 70% of the average penetration depth of decayed wood was used as the threshold value, resulting in a standard threshold of 25.5 to 29.8 mm. According to this standard, penetration depths greater than this threshold can be considered indicative of wood decay. The percentages of decayed areas relative to the cross-sectional areas were 67.7% (No.51), 51.1% (No.47), and 60.9% (No.86). It was observed that the 2D stress wave velocity tomography method had the highest percentage for evaluating decay in tree cross sections, followed by the drilling resistance method, with the pilodyn penetration method having the lowest percentage. The penetration depth grid maps indicated that both tomographic and drilling resistance methods tend to overestimate the area of decay. These threshold values can vary based on tree species, trunk conditions, detection techniques, and decay identification criteria, and may use either fixed or variable thresholds as a basis.

Pilodyn is a destructive test that can provide more accurate results in detecting decay area percentages of cross sections. However, the results from the borehole resistance method tend to overestimate the decay area. The decay area estimated using a sound speed of 1,400 m/s also overestimates the decay, while the decay area estimated by the instrument software tends to underestimate it, indicating that the standard reference value needs adjustment. The drilling resistance method is quick and easy to perform and interpret but only detects severe decay and cavities, requiring a control group (Li et al. 2022). On the other hand, acoustic tomography techniques are not accurate in diagnosing near-surface defects in a tree trunk, failing to provide precise information on the location and extent of decay and being ineffective in distinguishing between decayed wood and bacterial wetwood, or between decay and cavities (Soge et al. 2020). Therefore, it is recommended to consider integrating multiple tree detection methods to obtain more comprehensive data, which will improve the overall accuracy and reliability of the tests, while also adjusting the standard reference values.

Due to resource constraints, this study only used 3 Taiwan acacia trees decayed by G. australe. As such, this case study is intended as an exploratory preliminary study. This research can help generate new hypotheses that can be further tested and validated in future largescale studies. Although the sample size is small, the study may still reveal some preliminary results and trends, providing valuable references for future research.

In this study, to achieve tree risk assessment, visual inspection, acoustic tomography, drilling resistance, and pilodyn methods were used to detect the internal conditions of trees, thereby enhancing the understanding of the internal conditions of tree trunks decayed by G. australe. However, the percentage of decayed wood area relative to the cross-sectional area may be influenced by tree species, trunk shape, decay severity, moisture content, location, detection technology, and analysis methods. It may also be affected by the distribution of internal cellular structure, reaction wood, gravity, self-weight, moisture, and environmental conditions. Therefore, further in-depth research is needed to address these influencing factors in the future.

Conclusion

This study aims to understand the impact of G. australe fungal fruiting bodies on the internal wood decay of A. confusa trees and to use nondestructive techniques to inspect the cross sections of tree trunks, providing reference indicators for tree risk assessment. Various nondestructive methods were employed in this study, including stress wave technology, drilling resistance, visual inspection, and pilodyn penetration tests, to evaluate the internal decay condition of the trees.

  • By utilizing 2D stress wave velocity tomography, it is possible to preliminarily identify the severe areas and locations of decay. According to calculations after software operation, the estimated decayed areas were 54% (No.51), 47% (No.47), and 50% (No.86). Based on a standard threshold of 1,400 m/s for stress wave velocity, wood with a velocity below this value can be identified as decayed. In this study, the decay percentages of the cross sections of the 3 trees were 68.4% (No.51), 85.0% (No.47), and 65.4% (No.86).

  • The degree and relative location of wood decay were determined by analyzing the variations in the drilling resistance amplitude curves. Using 70% of the average drilling resistance amplitude of nondecayed wood as the threshold, the decay percentages were found to be 76.8% (No.51), 61.7% (No.47), and 67.3% (No.86).

  • Through visual and magnified inspection of the color and structure of the tree trunk cross sections, it was found that decay spreads from the sapwood to the heartwood, and there are reaction zone tissues indicative of the CODIT. The heartwood was more affected by decay compared to the sapwood.

  • This method measures the penetration depth of the pilodyn pin to assess the surface strength and decay degree of the wood. Using 70% of the average penetration depth of decayed wood as the threshold, the decay percentages were found to be 67.7% (No.51), 51.1% (No.47), and 60.9% (No.86).

Conflicts of Interest

The authors reported no conflicts of interest.

Acknowledgements

This research was supported by the Taiwan Forestry Research Institute (TFRI) project, for which we express our sincere gratitude [Project No.: 2024AS-7.4.2-F-01]. Thanks is given to the external financial support for the project entrusted to the TFRI. In addition, we would like to thank Mr. Tse-Yen Liu (Forest Protection Division, TFRI) for the confirmation of the fungus fruiting body Ganoderma australe.

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Detection of Ganoderma australe Decay in Three Acacia confusa Trees: A Case Study
Cheng-Jung Lin, Po-Hong Lin, Chieh-Yu Chang, Qi-Zhu Gong
Arboriculture & Urban Forestry (AUF) Mar 2025, 51 (2) 154-168; DOI: 10.48044/jauf.2025.003
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